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With the increasing integration of renewable energy sources such as wind and solar power, the regulation requirements of power systems have become more dynamic and complex. This paper provides a comprehensive review of multi-temporal scale regulation requirements and explores the application of diverse flexible resources across different time scales. The regulation demands are categorized into short, medium, and long-term scales, each presenting unique challenges that need to be addressed for efficient power system operation. Existing studies primarily focus on the adjustment of a single time scale, often overlooking the interplay between multiple time scales. This paper critically analyzes the limitations of previous approaches and demonstrates the need for more holistic and flexible solutions. The research results show that integrating diverse, flexible resources, including energy storage systems (ESS) and demand response (DR), can effectively meet regulation needs across various time scales. Additionally, the paper identifies the potential of hydrogen-based solutions to address emerging challenges in power system regulation. The findings highlight the importance of combining multiple flexible resources to improve system resilience and sustainability, offering a pathway toward more efficient and adaptable power systems. [ABSTRACT FROM AUTHOR]

For customer-oriented wood supply, buffering is required for flexibility to handle interactions in the wood procurement system. This includes balancing lead-time and operational cost by using stocks and production capacity as buffers. Despite the well-known challenge to balance the interactions between harvesting and forwarding in Nordic mechaniced CTL-operations, there has been limited research on how the machine groups can be staffed to enable flexibility and more focus on other measures to create flexibility. Therefore, this study explored trade-offs between wood lead-time and harvesting cost in the stump-to-roadside part of the wood supply chain by altering the numer of full-time working operators in the harvesting groups. This was done using discrete-event simulations implemented in Anylogic software. Input data included information about operational conditions in 1500 forest stands. The results revealed that the best balance was to have sufficient harvesting capacity to adjust wood lead times at the expense of increased harvesting costs. Of the tested options, the best balance was achieved when staffing a two-machine group with three operators, and thereby allocating 50% of the used work-shifts to regulating the field wood stock between the two machines. This resulted in the shortest lead times and the smallest harvesting cost increase. Compared to the option with no flexibility for stock adjustment (4 operators), the average lead-time could be reduced to one tenth at a cost increase of 3.4%. These findings have the potential to improve decisions of how harvesting groups are staffed to balance specific objectives of desired lead times and costs, which migh prove to be a valuable addition to the already used measures to manage wood flow. [ABSTRACT FROM AUTHOR]

The rapid development of new energy technology can make this type of energy the primary power source in the future. However, new energy power generation is considerably affected by the environment, resulting in intermittent and fluctuating characteristics. Given the shortage of power generation in urban distribution networks during extreme weather, a study on power supply restoration strategy considering flexible resource regulation ability is proposed in this study. First, the typical adjustable flexible resources, air conditioners, and electric vehicles in urban distribution networks are modeled, and their adjustment ability is evaluated. Second, on the basis of the evaluation results, the optimal power supply recovery path is solved to ensure the power supply of essential loads in the distribution network. Last, the IEEE 33‐bus system proves that this method can quickly find the optimal path of power supply recovery and effectively reduce the power loss rate of essential loads, thus improving the toughness of urban distribution networks. [ABSTRACT FROM AUTHOR]

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Vigorously developing flexible resources in power systems will be the key to building a new power system and realizing energy transformation. The investment construction cost and operation cost of various flexible resources are different, and the adjustment ability is different in different timescales. Therefore, the optimization of complementary allocation of various resources needs to take into account the economy and adjustment ability of different resources. In this paper, the global K-means load clustering model is proposed and the 365-day net load is reduced to eight typical daily net loads by clustering. Secondly, a two-level optimization model of flexible resource complementary allocation considering wind power and photovoltaic consumption is constructed. The flexible resources involved include the flexible transformation of thermal power, hydropower, pumped storage, energy storage, and demand response. The upper-layer model optimizes the capacity allocation of various flexible resources with the minimum investment and construction cost as the goal and the lower layer optimizes the operating output of various units with the minimum operating cost as the goal. The results of the example analysis show that the flexible capacity of thermal power units has nothing to do with the abandonment rate of renewable energy. As the abandonment rate of renewable energy decreases, the optimal capacity of pumped storage, electrochemical energy storage, and hydropower units increases. When the power-abandonment rate of renewable energy is 5%, the optimal allocation capacity of thermal power flexibility transformation, pumped storage, electrochemical energy storage, hydropower unit, and adjustable load in Province A is 5313, 17 090, 5830, 72 113, and 4250 MW, respectively. Under the condition that the renewable-energy abandonment rate is 0, 5%, and 10% respectively, the configured capacity of pumped storage is 20 000, 17 090, and 14 847 MW, respectively. [ABSTRACT FROM AUTHOR]

Abstract The rapid development of new energy technology can make this type of energy the primary power source in the future. However, new energy power generation is considerably affected by the environment, resulting in intermittent and fluctuating characteristics. Given the shortage of power generation in urban distribution networks during extreme weather, a study on power supply restoration strategy considering flexible resource regulation ability is proposed in this study. First, the typical adjustable flexible resources, air conditioners, and electric vehicles in urban distribution networks are modeled, and their adjustment ability is evaluated. Second, on the basis of the evaluation results, the optimal power supply recovery path is solved to ensure the power supply of essential loads in the distribution network. Last, the IEEE 33‐bus system proves that this method can quickly find the optimal path of power supply recovery and effectively reduce the power loss rate of essential loads, thus improving the toughness of urban distribution networks.

Vigorously developing new energy sources is an important approach to achieving the carbon peaking and carbon neutrality goals. However, the randomness, volatility, and intermittency of new energy pose severe challenges to the supply-demand balance and stability of the electric power system. Therefore, there is an urgent need to develop diversified flexible resources to guarantee the system’s safe and stable operation. This study summarizes the electricity demand and the power structure development pathways in China under the carbon neutrality goal. Based on this, it analyzes the different flexibility demands of electric power systems with different proportions of wind and solar power generation capacities and elaborates on the characteristics of various types of flexible resources needed for power generation, transmission, load, and storage from four aspects: peak capacity (adequacy), ramping flexibility, stability, and inertia. Drawing from the international experience regarding flexible resource development, we propose the principles for flexible resource development: supply security guarantee, low-carbon development, and economic optimization. Considering the existing problems in the flexible resource development in China, we propose a flexible resource development pathway that aligns with the emission reduction goal of the power sector and the medium- to long-term development trend of the electric power structure of China. Furthermore, key initiatives to ensure the development of flexible resources are proposed from five aspects: power source, power grid, load, energy storage, and market mechanism.

The rapid development of Internet and cloud computing technologies has led to the expansion of the scale of data centers, resulting in a continuous increase in the demand for data processing and storage. This not only results in higher energy consumption but also makes thermal management a key factor of energy management in data centers. A capacity configuration method is proposed for the core thermal management equipment of data center microgrids, electric boilers, cooling systems, and heat pumps. This method not only considers the uncertainty factors of the source and load but also effectively utilizes the characteristics of various flexible resources in data centers, such as the adjustable ability of different types of batch processing loads, air thermal inertia, and waste heat recovery, significantly improving the energy utilization efficiency and enhancing the system’s economy and flexibility. In addition, a wind power scenario generation method based on conditional least squares generative adversarial networks was proposed to improve the generation quality of wind power scenarios, and a random optimization model was constructed. Considering a certain province’s data center microgrid as a case study, the effectiveness of the model was verified, and a sensitivity analysis of the relevant parameters provided important references for microgrid planning. This study provides a new perspective and tool for the thermal management of data center microgrids and comprehensive utilization of renewable energy, which is of great significance for promoting the improvement of data center energy efficiency and sustainable development.

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the proportion of renewable energy installations in modern power systems increases, major weather events can easily trigger significant fluctuations in new energy generation and electricity load, presenting the system with the dual challenges of ensuring power supply and renewable energy consumption. Traditional dispatch models need more coordination and optimization of flexible resources under major weather events and risk management of system operations. This study focuses on provincial-level transmission systems, aiming to achieve the coordinated and optimized dispatch of flexible resources across multiple time scales in response to the complex and variable environments faced by the system. Firstly, by profoundly analyzing the response mechanisms of power systems during major weather events, this study innovatively proposes an event-driven day-ahead and intra-day optimal dispatch strategy for power systems. This strategy can sense and respond to major weather events in the day-ahead phase and adjust dispatch decisions in real time during the intra-day phase, thereby comprehensively enhancing the adaptability of power systems to sudden weather changes. Secondly, by considering the variability of renewable energy sources and electricity demand in the day-ahead and intra-day dispatch plans, the strategy ensures efficient and reliable power system operation under normal and major weather event scenarios. Finally, the method's effectiveness is validated using actual data from a provincial-level power grid in China. The proposed dispatch strategy enhances the resilience and adaptability of power systems to major weather events, which are becoming increasingly frequent and severe due to climate change. The research demonstrates that an event-driven day-ahead and intra-day optimal dispatch strategy can enhance the economic efficiency and robustness of power system operations through the coordinated dispatch of flexible resources during major weather events, thereby supporting the transition toward sustainable energy systems that are resilient against the challenges of a changing climate. [ABSTRACT FROM AUTHOR]

Abstract In recent years, distributed structures have been developed in distribution networks as a result of privatization as well as integration of independently operated distributed energy resources (DERs) into the grid. In this context, effective management techniques seem to be necessary to enable decentralized operation of systems that have been consisted of multiple agents. Accordingly, novel management schemes should be applied in such systems to enable the distributed reactive power management, which would finally improve voltage profile in the network. As a result, this paper develops a distributed algorithm for reactive power management in multi‐agent distribution systems with the aim of improving the voltage profile of the grid. Correspondingly, in the proposed framework, several cost functions are developed to model the effects of reactive power management on the system from the distribution system operator (DSO) as well as agents’ perspectives. Consequently, the proposed reactive power management algorithm would result in voltage profile improvement, while each agent of the system merely strives to maximize its own profits. Accordingly, the proposed scheme ensures the privacy of independent agents. Finally, the proposed scheme is applied on the modified IEEE‐37‐bus test system to investigate its effectiveness on Peer‐to‐Peer (P2P) reactive power management in multi‐agent systems.

With a large number of distributed energy resources connected to the grid,virtual power plants as a distributed energy management technology have received a lot of attention because of their flexibility,efficiency and sustainability. This paper briefly discussed the background of virtual power plants, analyzed the hot directions and emerging directions in virtual power plants,and introduced the composition and structure of virtual power plants. According to the different goals and functions of virtual power plants,virtual power plants can be divided into mission-driven virtual power plants, economy-driven virtual power plants and hybrid driven virtual power plants. On this basis, the different operation modes and different solution methods of different types of virtual power plants were further discussed. Finally,the future development prospects of virtual power plants were prospected.

Industries are undergoing low-carbon evolution with worldwide awareness of energy conservation. As the super key to processing it, integrated energy systems (IESs) are receiving more attention, in terms of cutting carbon emissions actively and passively. Until now, many well-established strategies have been proposed to low-carbonize IESs. However, issues still remain in implementing low-carbonization throughout the whole industry chain. In this context, critical technologies and available flexible resources at different levels of IESs, i.e., the transmission, distribution/district, and residential levels, are reviewed first in this paper. Then, flexible resources in the source, network, load, and storage are remodeled to minimize carbon emissions more directly. In this manner, CO2 in the whole industry chains of IESs can be marked and traced, which is named after the “all-carbon chain” here. Besides, as an original content of this paper, new technologies, i.e., CO2 flooding and Organic Rankine Cycle (ORC), get introductions for low-carbonizing IESs further. Last but not least, an actual large-scale IES is employed to verify the proposed approach from the transmission and distribution/district levels. It is concluded that the all-carbon chain is complex-less when applied in a bi-layer integration process and a weak-convex update formula also could ensure convergence (within 44 iterations). Besides, our approach helps to cut carbon emissions when compared with the traditional IES (by 50.61%) and two low-carbon IESs (by 18.37% and 12.09%). Moreover, our method makes IES enjoy a purposeful evolution for more functions of low-carbonization, source tracing, targeted evolution, and contribution quantification are covered.

The FlexPlan Horizon2020 project aimed at establishing a new grid planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the European Commission regulatory package "Clean Energy for all Europeans". FlexPlan creates a new innovative grid planning tool which is intended to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030-2040-2050), incorporation of full range of cost benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly RES and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. The final step in FlexPlan was formulating guidelines for regulators and planning offices of system operators, by indicating to what extent system flexibility can contribute to reduce overall system costs (operational and investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper focuses on the regulatory issues, which were uncovered during the initiation phase and of the project and refined in throughout six regional cases. In order to substantiate this, the paper explains in brief the developed and applied FlexPlan methodology and its testing in six regional cases.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The development of large-scale sustainable energy has affected the security of electricity systems. Virtual power plant (VPP) realize multi-energy synergistic complementation and efficient operation mainly with electricity. The paper proposed a flexible resource dynamic aggregation regulation method of VPP to ensure more renewable energy generation, which enables the efficient operation of multiple energy sources with electricity as the main source through collaborative and complementary measures. Firstly, the operating mode of VPP under market mechanisms is proposed, and the operating mechanism for VPP's participation in the market is established. Secondly, the types of flexible resources are identified, a cooperative game relationship between multiple autonomous agents within the power grid and VPP is formed to support an intelligent control method for VPP considering the complementarity of multiple energy sources and carbon emissions. Finally, a novel inverse cotangent compound differential evolution (NICCDE) algorithm is proposed by combining the innovative composite differential evolution algorithm with the tangent function, which realizes the flexible synergistic utilization of multiple energy sources. and reduces the training cost of the algorithm. Case studies from the conducted case study demonstrate the significant cost reduction achieved by the proposed method in comparison to conventional approaches when applied to VPP. Moreover, the utilization of this method enhances the precision and comprehensiveness of the search outcomes, thereby augmenting the overall effectiveness of the VPP system. [ABSTRACT FROM AUTHOR]

Driven by the carbon peaking and carbon neutrality goals, the power system is transforming to the new structure which is dominated by renewable energy and is facing a new supply-demand balance situation. Pumped storage, as the most mature energy storage technology at present, can provide flexible resources with different time scales to ensure the safety of the power system and promote the consumption of renewable energy. However, the operation strategy and cost sharing mechanism of the pumped storage station (PSS) are not clear, which hinders its further development under the new situation. In this context, the technical characteristics and functions of PSS are sorted out first. Then, the investment cost model is established from the perspective of the whole life cycle. After that, the evolution path of pricing mechanism and cost sharing mode are described in view of the different stages of electricity market development, providing a feasible scheme for the marketization of PSS. Finally, the future development of PSS is summarized and prospected.

The electricity-gas interconnected system includes the electricity and gas subsystems. It has a variety of energy coupling and storage devices with obvious differences in operation. And with the access of new energy power generation， the flexible and coordinated operation of the system is challenged. In this regard， an optimal scheduling method for integrated electricity-gas energy system using multiple time scales to call multiple types of resources is proposed. Firstly， a quasi-steady-state output model of energy equipment in the system is established. The proposed model takes the optimal daily operation cost of the system as the optimization goal， considers the different operation characteristics of energy sources and equipment， uses different time scales and step sizes to optimize the operation output of the power storage and other equipment， and dispatches different resources in the system in an orderly manner to fast track the fluctuations of the load and the new energy. Secondly， the random chance constraints are introduced to describe the remaining flexible resource supply capacity to improve the flexibility and robustness of the system. Finally， the distribution network and gas coupling system are used to conduct a case study to verify the effectiveness of the proposed method.

The FlexPlan Horizon2020 project aimed at establishing a new grid planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the European Commission regulatory package "Clean Energy for all Europeans". FlexPlan creates a new innovative grid planning tool which is intended to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030-2040-2050), incorporation of full range of cost benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly RES and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. The final step in FlexPlan was formulating guidelines for regulators and planning offices of system operators, by indicating to what extent system flexibility can contribute to reduce overall system costs (operational and investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper focuses on the regulatory issues, which were uncovered during the initiation phase and of the project and refined in throughout six regional cases. In order to substantiate this, the paper explains in brief the developed and applied FlexPlan methodology and its testing in six regional cases.

This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible resources and their aggregation technology. Utilizing network crawler technology within a knowledge graph framework, the research data pertinent to demand-side flexible resources and aggregation technology are extracted. These data undergo a meticulous cleaning process before being stored, culminating in the development of a knowledge graph tailored to the imaging and technology of demand-side flexible resources. The findings reveal a response rate of 7.25% ± 1.15%, with an uncertainty interval of 2.33%. Variations in air-conditioning load states appear to exert minimal impact on the response time lag. Following the issuance of a response signal, all systems can rapidly initiate appropriate response actions, demonstrating an uncertainty interval of approximately 52s±11s and 22s. The duration of the responses averages around 75s±11s, with an uncertainty interval of about 30s. This study fulfills the power system criteria for standards of demand-side flexible resources and augments the competitiveness of China’s power market.

In recent years, distributed structures have been developed in distribution networks as a result of privatization as well as integration of independently operated distributed energy resources (DERs) into the grid. In this context, effective management techniques seem to be necessary to enable decentralized operation of systems that have been consisted of multiple agents. Accordingly, novel management schemes should be applied in such systems to enable the distributed reactive power management, which would finally improve voltage profile in the network. As a result, this paper develops a distributed algorithm for reactive power management in multi‐agent distribution systems with the aim of improving the voltage profile of the grid. Correspondingly, in the proposed framework, several cost functions are developed to model the effects of reactive power management on the system from the distribution system operator (DSO) as well as agents' perspectives. Consequently, the proposed reactive power management algorithm would result in voltage profile improvement, while each agent of the system merely strives to maximize its own profits. Accordingly, the proposed scheme ensures the privacy of independent agents. Finally, the proposed scheme is applied on the modified IEEE‐37‐bus test system to investigate its effectiveness on Peer‐to‐Peer (P2P) reactive power management in multi‐agent systems. [ABSTRACT FROM AUTHOR]

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This paper provides an optimization strategy for flexible operation at the system level to guide the real-time flexible ramping of the power grid. Firstly, the concept of regional power grid flexibility is clarified, and the ramping factor is proposed as a flexibility metric. On this basis, taking the output priority of each node as the objective function and considering constraints such as line flow, power balance, and system flexibility, a mathematical model for regional power grid transmitting flexible power externally is proposed. Compared with the traditional models, this model focuses more on flexibility rather than economy. A case analysis based on the improved IEEE 30-Bus System verifies the feasibility and effectiveness of the proposed strategy and its advantages over the traditional models. [ABSTRACT FROM AUTHOR]

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the large-scale integration of wind power, photovoltaic power, and other new energy sources, their volatility and intermittency tend to cause the problem of flexibility imbalance in power systems. To make full use of the advantages of flexible resources on the new energy and load sides in power dispatching, an optimal scheduling method of flexible resources considering comprehensive user satisfaction is proposed in this paper. First, a demand response model considering comprehensive user satisfaction is constructed. Then, by taking into account the constraints of demand response and comprehensive user satisfaction, an optimal dispatching model of flexible resources on the source and load sides is established to achieve economic optimality. Finally, the case study based on the improved IEEE 30-bus system is carried out, and the simulation results under various scenarios verify the effectiveness of the proposed method.

Towards the dual-carbon goals, the new urban power grid (NUPG) dominated by new energy has a low proportion of adjustable power generation units, resulting in insufficient scheduling flexibility. As a result, it becomes challenging to cope with the complex operating conditions of the NUPG. In this paper, after analyzing the new operational characteristics and challenges of the NUPG, a flexible load dispatching architecture and key technologies for the NUPG are proposed. These enhance the scheduling flexibility of the NUPG from the load side, which further provides support for the operation of the large power grid. Then, the types of scheduling objects, scheduling methods, scheduling tasks, and four essential dispatching technologies are introduced to provide a reference for building the NUPG flexible load dispatching system. Finally, the effectiveness of the NUPG flexible dispatching architecture and technologies is verified by simulation analysis of the IEEE39-bus system and the actual power grid in East China.

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The traditional power distribution network is transitioning to an active electrical distribution network due to the integration of distributed energy resources. Simultaneously, the increasing occurrence of extreme weather requires power networks to be more resilient. Distributed energy resources, especially mobile energy storage systems (MESS), play a crucial role in enhancing the resilience of electrical distribution networks. However, research is lacking on pre-positioning of MESS to enhance resilience, efficiency and electrical resource utilization in post-disaster operations. To address these issues, this paper introduces a proactive MESS pre-positioning method in active electrical distribution networks considering the uncertainties of distributed generation output. Firstly, the flexible resources in active distribution networks are modeled, including distributed generation, MESS and Electric Vehicles. Then, a robust optimization model is established for the pre-positioning of MESS considering the PV output uncertainty, where the big-M method and the column constraint generation algorithm are used to calculate the optimal capacity and location of the MESS. Finally, the effectiveness of the MESS pre-positioning model is verified using the IEEE 33-node system and the IEEE 141-node system, respectively. The simulation results show that the load loss at most of the nodes is significantly reduced and the total system cost is reduced by 17.65% compared with the case of fixed MESS access location. The results also show that when the number of MESS is low, each additional MESS unit reduces the total load shedding cost by about 20%. Moreover, the proposed robust optimization model for MESS pre-positioning is also effective in large-scale systems. • Establishing a pre-positioning method for mobile energy storage systems. • Modeling flexible resources and analyzing their supply capabilities. • Coordinating the operation of mobile energy storage systems with other flexible resources. • Enhancing the resilience of the distribution network through bi-level optimization. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The development of renewable energy is of great significance to relieve the pressure on the energy supply and promote the low-carbon operation of the power system. However, the volatility of renewable energy, especially wind and solar energy, has a great impact on the safe and reliable operation of the power system. If we want to introduce renewable energy and ensure the safe and reliable operation of the power system, it is necessary for the power system to provide enough flexibility. Northwest China is rich in natural resources and an important area of power supply in China, which also faces the problem of insufficient flexibility. Therefore, based on the power system development and natural conditions in northwest China, this paper studies the key factors affecting the flexibility of the power system when renewable energy accounts for a large proportion, and proposes measures to improve the flexibility of the power system by using the power system optimization tool Flextool developed by IRENA. [ABSTRACT FROM AUTHOR]

• A new approach to formulate expected security cost dynamic optimal power flow (ESCDOPF) problem by incorporating solar energy and flexible resources is presented. • Due to the non-linear, non-convexity of the ESCDOPF problem, a "Novel Differential Evolution" (NDE) algorithm is proposed for solving. • Preventive/corrective control measures with solar energy and flexible resources is studied. • Different scenarios with different case studies on a modified IEEE-30 bus system are conducted. Numerous power systems are undergoing dramatic changes in their generation portfolios. Solar electricity generation capacity has increased significantly in response to global environmental and national energy security concerns, as well as rising fuel prices. Integration of these solar resources with limited dispatchability into existing power systems with varying levels of availability, demand and system flexibility is challenging. This article proposes an expected security cost dynamic optimal power flow (ESCDOPF) that integrates solar and flexible resources. The proposed model is formulated and implemented with a "Novel Differential Evolution (NDE)" optimization algorithm to obtain the global solution for the total expected system operating cost which includes contingency costs by satisfying the model constraints over a day. Solar output is predicted using the Beta probability distribution function with direct, under-estimation and over-estimation costs. Similarly, flexible resources such as demand response management (DRM), battery energy storage systems (BESS) and high-voltage direct current (HVDC) systems are modelled in order to manage the supply-demand portfolio at all times. To handle inequality constraints and feasible solution superiority, this NDE algorithm employs a penalty function method. To validate the proposed model and the solution process, illustrative cases of various scenarios are performed on an IEEE-30 bus system. Results show that the proposed NDE algorithm satisfies all of the model constraints and also provides cost savings from the integration of solar and flexible resources into the power system. [ABSTRACT FROM AUTHOR]

Recently, due to the restructuring of power systems and the high penetration level of local renewables, distribution systems have encountered with the complexity of power management. Therefore, the modern systems would be operated in a multi-agent structure which facilitates the power management as well as privacy protections of independent entities. In this structure, the distribution system is assumed to compose of several agents who independently schedule their local resources in order to maximize their own profits. Consequently, this paper provides an efficient peer-to-peer (P2P) active power management framework in a multi-agent distribution system while considering network constraints (i.e., line loadings and losses). In this context, in the proposed P2P scheme, the distribution system operator (DSO) model the network constraints in the form of line-usage costs within the transactive signals. Respectively, the developed transactive control signals enable the DSO to model the power loss as well as alleviate the congestion in the grid. Therefore, the agents automatically consider the network constraints in their power transactions management procedure without any direct interferences of the DSO in their resource scheduling. Finally, the proposed model is implemented on the modified-IEEE-37-bus-test system in order to investigate its effectiveness in the energy management of multi-agent systems. [ABSTRACT FROM AUTHOR]

Current electricity markets are not moving fast enough towards decarbonization, nor are they ensuring the economic sustainability of the different supply technologies in the short-term –cannibalization and depredation problems–. To solve these problems, this study presents an innovative market design to achieve a sustainable electricity system based on cleaner production. Based on the assumption that the energy supplied by manageable and non-manageable generators can be considered as two different goods, we propose a two-market system within the day-ahead market where non-manageable generators operate in the first market through long-term contracts and manageable generators operate in the (marginalist) second market. Under this system, the regulator appropriates an economic surplus that is given by the difference –produced in the first market– between what is received from the buyers in this market (second market's equilibrium price) and what is paid to each non-manageable generator (levelized cost of energy). This public surplus will be used to cover part of the regulated costs of the electricity system, lowering the final price of electricity. To simulate empirically our two-market design, we use hourly microdata from the supply and demand curves of the Iberian day-ahead market. The results of this case study are promising, showing a decrease in the electricity prices and CO 2 emissions, an increase in the amount of energy exchanged and the obtainment of a surplus for the regulator of 5,753 M€ in 2021 and 9,944 M€ in 2022. The proposed design ensures the economic sustainability of intermittent renewables as well as provides signals for long-term investment in the deployment of flexible carbon-free resources. • A new market design is proposed that allows reducing electricity prices and CO 2 emissions. • All near-zero marginal cost units ensure their economic sustainability. • Flexible resources are not affected by price regulation. • The electricity regulator obtains an economic surplus. • It does not create inefficiency to prioritize the dispatch of renewables. [ABSTRACT FROM AUTHOR]

The distribution system is undergoing profound transformations with decarbonization efforts through the rapid integration of renewable energy and the consequent transition of the distribution network from passive to active. Nonetheless, environmental and economic urgency requires redesigning the existing distribution system. New operational standards and technologies such as electric vehicles, demand response, energy storage systems, energy hubs, microgrids, and transactive energy markets have been developed. Distribution system expansion planning plays a crucial role in supporting this transition process. This work presents a review of planning proposals published in the last decade considering flexibility, local markets, and microgrid concepts. The main aspects of these works are described in terms of solution methods, expansion alternatives, planning periods, uncertainties, and contributions, among others. Furthermore, planning proposals are analyzed and classified taking into account new market designs. In addition, future trends are identified. Finally, this review can be used as a tool and guide for different stakeholders on current practices and new trends regarding the distribution system expansion planning, serving as a foundation for future investigations. • Growing trend of research focused on distribution planning with energy markets. • Mathematical programming is the most used solution method for distribution planning. • New methods must be developed to deal with the complexity of distribution planning. • Non-network solutions may avoid or defer investments in distribution systems. [ABSTRACT FROM AUTHOR]

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The consumption of traditional fossil energy brings inevitable environmental protection problems, which also makes the low-carbon transition in industrial development imminent. In the process of low-carbon transition, the power industry plays a very important role. However, the large-scale integration of renewable energy resources such as wind power and photovoltaic brings new characteristics to power system dispatch. How to design a dispatch strategy that considers both low-carbon demand and economic cost has become a major concern in power systems. The flexible resources such as demand response (DR) and energy storage (ES) can cooperate with these renewable energy resources, promoting the renewable energy generation and low-carbon process. Thus, a low-carbon dispatch strategy for power systems considering flexible DR and ES is proposed in this article. First, models of DR and ES based on their behavior characteristics are established. Then, a carbon emission index is presented according to China’s Clean Development Mechanism (CDM). Finally, the low-carbon dispatch strategy for power systems is proposed through the combination of the carbon emission index and flexible resource dispatch models. The simulation results show that the proposed dispatch strategy can significantly improve wind power consumption and reduce carbon emission.

Flexible job shop scheduling problem is one of the most important topics in production management and is one of the most complex topics in combinatorial optimization. This problem is a generalization of job shop and parallel machines scheduling problem. Since the efficient allocation of resources can improve the performance of manufacturing, here, to reduce the processing time of jobs, additional resources are assigned to machines. In fact, in this paper, the effect of flexible resources in the flexible job shop scheduling problem with unrelated parallel machines and sequence-dependent setup time is investigated. Also, by presenting a mixed-integer linear programming model, an attempt has been made to minimize the costs of makespan, total weighted tardiness, delivery time and inventory. After solving this model by the GAMS, due to the NP-hardness of the problem, a tabu search (TS) algorithm is utilized for large-size instances. Finally, the obtained results are compared with the genetic algorithm (GA). To verify the statistical validity of the computational experiments and confirm which the best algorithm between the TS algorithm and GA is, a Kruskal–Wallis test is used. The results show that the TS algorithm is better than the GA. [ABSTRACT FROM AUTHOR]